This cluster provides guides on fine-tuning Large Language Models (LLMs) and explores alternative methods for grounding LLMs with external knowledge. The fine-tuning guides cover local methods using techniques like LoRA, QLoRA, and Unsloth with Ollama, as well as using PyTorch and Hugging Face. Additionally, one article introduces Cache-Augmented Generation (CAG) as a simpler alternative to Retrieval-Augmented Generation (RAG) for grounding LLMs, particularly when knowledge bases fit within the model's context window. AI
IMPACT Provides practical guidance for developers on customizing LLMs and improving their knowledge integration capabilities.
RANK_REASON The cluster consists of guides and explanations of techniques for fine-tuning and grounding LLMs, which are tools and methods rather than a new frontier release or significant industry event.
Read on Medium — fine-tuning tag →
- Llama
- Phi-2
- Hugging Face
- PyTorch
- Cache-Augmented Generation
- Calibration Aware Generation
- ChatGPT
- Lora
- Ollama
- QLoRA
- retrieval-augmented generation
- Unsloth
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